1
|
Chen BH, Hivert MF, Peters MJ, Pilling LC, Hogan JD, Pham LM, Harries LW, Fox CS, Bandinelli S, Dehghan A, Hernandez DG, Hofman A, Hong J, Joehanes R, Johnson AD, Munson PJ, Rybin DV, Singleton AB, Uitterlinden AG, Ying S, Melzer D, Levy D, van Meurs JBJ, Ferrucci L, Florez JC, Dupuis J, Meigs JB, Kolaczyk ED. Peripheral Blood Transcriptomic Signatures of Fasting Glucose and Insulin Concentrations. Diabetes 2016; 65:3794-3804. [PMID: 27625022 PMCID: PMC5127245 DOI: 10.2337/db16-0470] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Accepted: 09/04/2016] [Indexed: 01/09/2023]
Abstract
Genome-wide association studies (GWAS) have successfully identified genetic loci associated with glycemic traits. However, characterizing the functional significance of these loci has proven challenging. We sought to gain insights into the regulation of fasting insulin and fasting glucose through the use of gene expression microarray data from peripheral blood samples of participants without diabetes in the Framingham Heart Study (FHS) (n = 5,056), the Rotterdam Study (RS) (n = 723), and the InCHIANTI Study (Invecchiare in Chianti) (n = 595). Using a false discovery rate q <0.05, we identified three transcripts associated with fasting glucose and 433 transcripts associated with fasting insulin levels after adjusting for age, sex, technical covariates, and complete blood cell counts. Among the findings, circulating IGF2BP2 transcript levels were positively associated with fasting insulin in both the FHS and RS. Using 1000 Genomes-imputed genotype data, we identified 47,587 cis-expression quantitative trait loci (eQTL) and 6,695 trans-eQTL associated with the 433 significant insulin-associated transcripts. Of note, we identified a trans-eQTL (rs592423), where the A allele was associated with higher IGF2BP2 levels and with fasting insulin in an independent genetic meta-analysis comprised of 50,823 individuals. We conclude that integration of genomic and transcriptomic data implicate circulating IGF2BP2 mRNA levels associated with glucose and insulin homeostasis.
Collapse
Affiliation(s)
- Brian H Chen
- Longitudinal Studies Section, Translational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA
- Diabetes Research Center, Department of Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Marjolein J Peters
- Department of Internal Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
- Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging, Leiden and Rotterdam, the Netherlands
| | - Luke C Pilling
- Epidemiology and Public Health Group, Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, U.K
| | - John D Hogan
- Program in Bioinformatics, Boston University, Boston, MA
| | - Lisa M Pham
- Program in Bioinformatics, Boston University, Boston, MA
| | - Lorna W Harries
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, U.K
| | - Caroline S Fox
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Stefania Bandinelli
- Geriatric Rehabilitation Unit, Azienda Sanitaria di Firenze, Florence, Italy
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Dena G Hernandez
- Laboratory of Neurogenetics, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD
| | - Albert Hofman
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Jaeyoung Hong
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Roby Joehanes
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD
- Hebrew SeniorLife, Harvard Medical School, Boston, MA
| | - Andrew D Johnson
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Peter J Munson
- Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, MD
| | - Denis V Rybin
- Data Coordinating Center, Boston University, Boston, MA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
- Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging, Leiden and Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Saixia Ying
- Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, MD
| | | | - David Melzer
- Epidemiology and Public Health Group, Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, U.K
| | - Daniel Levy
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
- Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging, Leiden and Rotterdam, the Netherlands
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Jose C Florez
- Diabetes Research Center, Department of Medicine, Massachusetts General Hospital, Boston, MA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA
- Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Josée Dupuis
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - James B Meigs
- Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Eric D Kolaczyk
- Program in Bioinformatics, Boston University, Boston, MA
- Department of Mathematics and Statistics, Boston University, MA
| |
Collapse
|